[1]} propose Recurrent CNN RoBERTA (RCNN-RoBERTa), a hybrid neural architecture building on RoBERTA architecture, which is further enhanced with the employment and devise of a recurrent convolutional neural network. They report a performance with an accuracy of %79 on SARC dataset [2]}. Similarly, [3]} use an ensemble of RoBERTa and ALBERT [4]} on Get it #OffMyChest dataset [5]} achieve a performance of %85 accuracy with \(F1\)  score of 0.55. [6]} use BERT along with aspect-based sentiment analysis to extract the relation between context dialogue sequence and response. They obtain an F1 score of 0.73 on the Twitter dataset and 0.73 over the Reddit datasetTwitter and Reddit datasets used for in this study were provided in the shared task on Sarcasm Detection, organized at Codalab.. We expect to see more studies geared toward leveraging pre-trained contextual embeddings and transformers toward sarcasm detection in the upcoming years.
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